You already said yes in the group chat — so this isn't an invitation, it's the briefing. I coach professionals in AI skills, and I'm running that same curriculum for my own people as a free live workshop: small sessions on Zoom — one or two of you at a time — two 2-hour sessions, the same material my paying students get. Not a sample. Not a trial. The real thing — because you're my people, and because, honestly, you'll be teaching me something too.
You get: real, hands-on AI skills — the same method and materials my paying mentees get, at whatever pace fits your life, on whatever you actually care about: work, a side project, travel planning, the family photo archive, anything.
I get: a teacher's most valuable thing — honest students. Every session with you teaches me how AI actually lands with real people outside the tech bubble: what confuses, what excites, what feels creepy, what your workplace allows, what you'd genuinely pay for. That knowledge directly shapes what I teach next and to whom. You're not a guinea pig — you're a co-designer. And I'll tell you exactly what I'm learning from you as we go.
My own design, and the spine of everything I teach: the five things a company does to ship a product — Discussion, Design, Develop, Deployment, Debugging — compressed onto one desktop, with AI doing the heavy lifting and you keeping the judgment. You don't need to code. You don't need to be "technical." You need curiosity and a browser.
Get answers that land right the first time
Check the facts, decide what gets built
AI builds from your instructions
Test it, then make it real
Find out why, when AI gets it wrong
Let the AI interview you before it answers — and keep the verification habits that stop you trusting it blindly. The difference between generic fluff and output you can actually use.
Teach the AI who you are, how you work, and what you're really asking — including handing it your own documents so it answers from your material instead of guessing from whatever it half-remembers. This is what turns it into a competent helper for your life and job, and it keeps teaching you long after our sessions end.
Go from chatting with AI to directing it: hand a whole job to an AI agent, let it work, and verify what comes back. This is the part most people have already paid for and never use.
The full program runs five belts. Our two sessions take you hands-on through the first three — everything most people need day to day — and close with a look over the fence at the fourth.
We start wherever you are — total beginner is the most common starting point and honestly my favorite. And if all you want from the whole thing is Session 1's "make AI useful and stop worrying about it," that's a complete, perfect outcome too.
Maybe you think AI is overhyped, creepy, coming for jobs, or all three. I'm not going to talk you out of any of that — some of it is true, and the people most worried about AI are usually the ones paying closest attention.
What I'll show you instead is where it breaks, where it lies, what it should never be trusted with, and how to use it on your terms with your privacy intact. Skeptics make my best students — and your skepticism is, sincerely, part of what I want to learn from.
Here's the thing almost nobody knows: the $20-a-month AI subscription most people already have is a professional-grade toolkit, and the overwhelming majority of subscribers never leave the chat box. They're paying for a workshop and using the doorbell. A large part of these two sessions is simply showing you what's already yours.
Beyond the chat window sit agent workspaces that take a whole job and go do it — research, files, spreadsheets, multi-step work. Same plan. No upgrade. Most people have never clicked them.
A permanent workspace stocked with your documents, your style, your standing instructions. Ask a question there and it answers from the material you handed it rather than from a hazy memory of the internet — the industry calls this RAG, and it's the most dependable way to keep answers anchored to something real. You stop re-explaining yourself, and it stops guessing.
Hook it up to the places your actual work lives, hand it real documents, and let it produce real files back — not just text you copy-paste and reformat by hand.
Knowing which model to reach for — and when the cheap fast one is genuinely the right answer — is most of the difference between a $20 plan that feels tight and one that feels generous.
We'll all work on Anthropic's Claude Pro for these sessions, for one practical reason: Pro already includes the advanced features — the agent surfaces, the projects, the connectors, the developer tooling. There's no "but that's the higher tier" moment mid-lesson. If you ever need more headroom, you simply top up credits rather than buying your way up a ladder of plans. For a class, that means everyone sees the same screen and nobody gets fenced out.
The skills transfer — including off the paid track entirely. What you learn here — how to frame a request, how to give the AI proper context, how to hand off a whole job and then verify what comes back — works on ChatGPT and Gemini, and it works just as well on the open-source stacks: OpenClaw, Hermes, and open-weight models you can run on your own machine with no subscription at all. The buttons move; the method doesn't. I teach the method precisely so you're never stranded when your employer standardizes on a different vendor, when a budget gets cut, or when something better launches next year. Loyalty to a method, not to a logo.
Once you know what you're doing, you'll notice most everyday AI work doesn't need the most expensive model available. Matching the model to the job is most of the difference between a plan that feels tight and one that feels generous — and some of the best value sits in newer, far cheaper models most people have never heard of.
Which ones — and the rules for using them safely — I'll post to the group chat separately. They're genuinely useful and genuinely conditional: where your words end up, what your employer allows, and what should never go near them. That belongs in a conversation with rules attached, not a line on a page.
No mystery jargon. These are the actual pieces on the table, and where each one sits.
Why show the open-source ones at all when the paid tools are easier? Because seeing the same idea in two very different implementations is what turns a tool you memorized into a concept you understand — and because knowing what's free matters when a budget gets cut or an employer says no. The same goes for the pay-per-use and broker layers: once you've seen that the monthly plan, the direct API and the gateway are three doors into the same room, you stop being a customer of one product and start choosing on the merits.
Some of you have known me forever and have no idea what I actually do all day. Here it is, briefly.
Twenty-five years as an engineer in Silicon Valley — hardware validation, software QA, and network engineering across R&D labs and consulting contracts where "we'll ship it next quarter" was never an acceptable answer. My job, for a quarter century, was finding out why things break.
I've lived through four technology disruptions: the dot-com bust, the telecom collapse, outsourcing, and offshoring. AI is the fifth, and I'm getting through it the same way I got through the others — by learning faster than the disruption moves. That system is what I'm teaching you. The engineers who survived each wave weren't the ones who memorized a platform; they were the ones who had a method for putting new tools to work quickly.
Sessions in English · Mandarin · Cantonese · Zoom or Google Meet · US and Asia-Pacific friendly hours
You said yes in the group chat. There's nothing to sign and nothing to pay — that part is finished.
Getting everyone onto one weekend turned out to be impossible — some of you can only do weekdays, some only weekends. So there's no single date any more. I'll send a Calendly link to the group; pick the two times that actually suit you.
Bring a laptop, not a phone — you'll want a real keyboard. Have a free AI account ready if you can; if that sentence worries you, message me and we'll sort it in five minutes.
Hands-on from minute one — you drive your own keyboard while I coach. White through Green Belt, closing with the live demo.
What worked, what confused you, what your workplace really thinks of AI. That's the gift back — and it's plenty.
Life happens. If you make the first session but not the second, or drift off halfway, nothing changes between us. If you'd rather just have coffee and never talk about AI again, we're square. This is a standing offer, not a commitment — the relationship always outranks the project.
Purple hands-on — and Brown beyond it — is where the work leaves the chat window entirely: your own server on the internet, run by agents you command, hosting something real that you built. That's how I built my Award Transfer Optimizer, with the same method you'll learn in our two sessions.
It can't be group work, because the environment has to exist first: a Linux cloud VM with remote desktop — a second computer of your own that lives in a data centre instead of on your desk, always on, used from your laptop. Standing it up is realistically two sessions, done together at your pace, and none of it is knowledge you need in advance.
Most people won't need this, and that's genuinely fine — the two sessions stand on their own. It isn't part of the gift and it isn't group work: it's a separate arrangement, made offline, one person at a time. If it's the direction you want to go, we can arrange for 1-on-1 sessions.
One big group on a single weekend was never going to work — some of you can only do weekdays, others only weekends. So you pick your own times instead. I'll send a Calendly link to the group chat: choose two 2-hour slots that suit you, and either come on your own or put two of you on the same booking. You're the first batch, so you get first pick of the calendar.
Questions before we start, or something you're quietly hoping we'll cover? Send it to the group, or to me directly. Requests shape the sessions — that's not a courtesy, it's how I find out what to teach.